Nathanael Bosch

I am a PhD student in machine learning at the University of Tübingen and the International Max Planck Research School for Intelligent Systems (IMPRS-IS), supervised by Philipp Hennig. My research mostly focuses on probabilistic numerics for differential equations, where I treat numerical solvers themselves as probabilistic inference with the goal to develop methods that provide efficient quantification of numerical error and enable new ways to do data-driven inference in dynamical systems.

I also like to make my research widely accessible in the form of open-source software, for example via ProbNumDiffEq.jl which provides efficient probabilistic numerical differential equation solvers in Julia.